Saturday, March 6, 2010

The D'Aleo/Watts report has come under justified criticism for it's silly claims about marching thermometers etc, amplified into claims about malfeasance by various scientific groups.

But there's one little thing that particularly bugs me, because I have pointed it out more than once, but it makes no difference. They say

"See the huge dropout of data in Africa, Canada and Siberia in the two maps from NASA GISS
with 250 km smoothing from 1978 to 2008"

and show these pictures:

Well, yes, quite a reduction in going from 1978 to 2008. But actually, if you go to the GISS site and ask for April 2008, what you see is not nearly as sparse.

So what is going on?

I managed to track down where the SPPI image came from. Bob Tisdale has a version of it in a post dated May 20 2008. It's an early version (current when he posted it), made with an early batch of data that came in for that month. And it's compared with the full version of April 1978.

Steven, I don't see how that applies here. Watts and D'Aleo didn't handle any data, so what could they post? And GISS does post the data that goes with every one of these graphs. They give the gridded data with the plot, and elsewhere you can get the station data they used.

CE, it may not be intentional. But they didn't go to the website, at least not while preparing the report - otherwise they would have got the one I got (which was there back in October, when I first complained about d'Aleo's use of it). What I presume is that he had a plot on file, and at some stage looked at it and said "Wow, what a contrast", without checking on why. After all, why choose April 2008 in 2010?

If they wrote the paper to my standards, they would have had to supply the data behind that figure ( copy it from the web site with a time stamp) and they would have had to supply the code that drew the graphic.Oh, nasa do change that code without notices.

Another way around this is to pt time stamps and version control information into the graphics. So when a program puts out a graphic on the web, you got some traceability to the source data and version of the software embedded in the graphic. I've worked in applications where every graphic had to have Graph produced by : program V5.12 data: 3dt5x Time: blah blah blah.

that way somebody reading your report could understand 10 years later why you ran a standard model ( say Modtran) with the same dataand got a different answer. It's all about traceability. I cant count the number of time whole reports had to be done over because the first set of graphs were produced. Then the writing commences. Then Somebody fixes a bug. and they forget to regenerate all the figures.

But not the place to argue this. Just saying other fields do this with no trouble at all.

Anyways, the paper in question is questionable for a bunch of other reasons

http://scienceofdoom.com - all climate science, but quite uninterested in surface temperature effects, as you can see in http://scienceofdoom.com/2010/03/02/why-global-mean-surface-temperature-should-be-relegated/

Carrick,I haven't counted cells. One of the reasons I first complained with G'Aleo's post was that he made a point of the lack of coverage of Canada. The correct graph does much better. Australia, West Africa are better covered.

D'Aleo/Watts could still put their argument based on the correct plots. We'd see it in proper proportion.

I think it's somewhat important to try to get these furphies out of the discourse. As this example shows, they are pushed hard.

Nick, I agree and start by saying they should start with the correct data, rather than just rely on figures of questionable providence to make their case for them.

Then they shouldn't rely on these graphs exclusively to make their point. As I see it, the relevant question is "what percent of the surface area of Africa is not covered by stations?"

That said, there is a fair amount of Africa missing, visually it appears to be well over half. But even that isn't enough to justify all of their bluster.

It isn't that hard to bound the uncertainty associated with the missing regions. At the least they should have shown how much the uncertainty of the final answer (which is global temperature trend 1951-current I suppose) is influenced by these missing measurements.

Just saying there are warts in data is in itself not very interesting.